Coursera The Data Scientist’s Toolbox

Coursera The Data Scientist’s Toolbox – quiz answers to all weekly questions (weeks 1-4):

Week 1: Data Science Fundamentals
Week 2: R and RStudio
Week 3: Version Control and GitHub
Week 4: R Markdown, Scientific Thinking, and Big Data

You may also be interested in Google Data Analytics Professional Certificate Course 1: Foundations – Cliffs Notes.

Coursera The Data Scientist’s Toolbox quiz answers

Week 1: Data Science Fundamentals quiz answers

In this module, we’ll introduce and define data science and data itself. We’ll also go over some of the resources that data scientists use to get help when they’re stuck.

Question 1. Which of these is NOT one of the main skills embodied by data scientists?

Artificial intelligence
Hacking skills
Substantive expertise

Question 2. What is the most important thing in Data Science?

The question you are trying to answer
Statistical inference
Working with large data sets

Question 3. Which of these might be a good title for a forum post?

URGENT! R isn’t working!
Removing rows with NAs in data.frame using subset(), R 3.4.3
How do I get rnorm() to work?

Question 4. What’s the first step in the data science process?

Communicate your findings
Exploring the data
Generating the question

Question 5. Which of these is an example of a quantitative variable?

Latitude
Occupation
Educational level

Week 2: R and RStudio quiz answers

In this module, we’ll help you get up and running with both R and RStudio. Along the way, you’ll learn some basics about both and why data scientists use them.

Question 1. What does base R focus on?

Mapping
Statistical analysis
Artificial intelligence

Question 2. What is RStudio?

A graphical user interface for R
Version control software
A programming language

Question 3. What is the name of the quadrant in the bottom left corner of RStudio, in the default layout?

History
Plots
Console

Question 4. What command lists your R version, operating system, and loaded packages?

versions()
Sessioninfo()
sessionInfo()

Question 5. What file extension do Projects in R use?

.Rproj
.R
.RPROJECT

Week 3: Version Control and GitHub quiz answers

During this module, you’ll learn about version control and why it’s so important to data scientists. You’ll also learn how to use Git and GitHub to manage version control in data science projects.

Question 1. What is a good example of a message to accompany a commit?

Modified linear model of height to include new covariate, genotype
Fixed problem with linear model
Updated thing

Question 2. On each repository page in GitHub, in the top right hand corner there are three options. They are:

Watch, star, fork
Pull, clone, fork
Commit, contributors, issues

Question 3. Which of the following will initiate a git repository locally?

git init
git remote add
git boom

Question 4. What is the order of commands to send a file to GitHub from within RStudio?

Commit > Push
Stage > Commit message > Commit > Push
Pull > Push > Commit

Question 5. How do you add all of the contents of a directory to version control?

git add .
cd ~/dir/name/of/path/to/file
git commit -m “Message”

Week 4: R Markdown, Scientific Thinking, and Big Data quiz answers

During this final module, you’ll learn to use R Markdown and get an introduction to three concepts that are incredibly important to every successful data scientist: asking good questions, experimental design, and big data.

Question 1. What is the format for including a link that appears as blue text in your markdown document?

[text that is shown](link.com)
(link.com)[text that is shown]
(text that is shown)[link.com]

Question 2. Which of the following describes a predictive analysis?

Using data collected in the past to predict values in the future
Finding if one variable is related to another one
Showing the effect on a variable of changing the values of another variable

Question 3. We collect data on all the songs in the Spotify catalogue and want to summarize how many are country western, hip-hop, classic rock, or other. What type of analysis is this?

Exploratory
Descriptive
Predictive

Question 4. What might a confounder be in an experiment looking at the relationship between the prevalence of white hair in a population and wrinkles?

Age
Socioeconomic status
Sex

Question 5. Which one of the following is an example of structured data?

The text from a series of books
Lung x-ray images
A table of names and student grades

Peer-graded Assignment: Assemble your toolbox

PROMPT
Set up a Github account (you may use your own name or a pseudonym).
Create a repo called datasciencecoursera.
Copy and paste the link to your GitHub account (or a direct link to your datasciencecoursera repo).

https://github.com/CP-Tadeo

PROMPT
Create a text file called HelloWorld.md
Add the line “## This is a markdown file” (without the quotation marks) to the document.
Push the document to the datasciencecoursera repo you created on Github.
Submit the link to the HelloWorld.md file on your Github repo.

https://github.com/CP-Tadeo/datasciencesoursera

PROMPT
Fork the data sharing repository here:
Copy and paste the link to the forked repository on your Github account.

https://github.com/jtleek/datasharing

Coursera The Data Scientist’s Toolbox quiz answers

Week 1: Data Science Fundamentals quiz answers

Week 2: R and RStudio quiz answers

Week 3: Version Control and GitHub quiz answers

Week 4: R Markdown, Scientific Thinking, and Big Data quiz answers

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